• DocumentCode
    2778489
  • Title

    Creating 3D models with uncalibrated cameras

  • Author

    Han, Mei ; Kanade, Takeo

  • Author_Institution
    Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    178
  • Lastpage
    185
  • Abstract
    We describe a factorization-based method to recover 3D models from multiple perspective views with uncalibrated cameras. The method first performs a projective reconstruction using a bilinear factorization algorithm, and then converts the projective solution to a Euclidean one by enforcing metric constraints. We present three factorization-based normalization algorithms to generate the Euclidean reconstruction and the intrinsic parameters, assuming zero skews. The first two algorithms are linear, one for dealing with the case that only the focal lengths are unknown, and another for the case that the focal lengths and the constant principal point are unknown. The third algorithm is bilinear dealing with the case that the focal lengths, the principal points and the aspect ratios are all unknown. We present the results of applying this method to building modeling, terrain recovery and multi-camera calibration
  • Keywords
    image reconstruction; terrain mapping; 3D models; Euclidean reconstruction; bilinear factorization; building modeling; intrinsic parameters; multi-camera calibration; multiple perspective views; projective reconstruction; terrain recovery; uncalibrated cameras; Calibration; Cameras; Image reconstruction; Image sequences; Iterative algorithms; Robot vision systems; Robustness; Shape; Singular value decomposition; Subspace constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Computer Vision, 2000, Fifth IEEE Workshop on.
  • Conference_Location
    Palm Springs, CA
  • Print_ISBN
    0-7695-0813-8
  • Type

    conf

  • DOI
    10.1109/WACV.2000.895420
  • Filename
    895420